At an upstate New York zoo in 2012, an olive baboon sat with her baby at a table opposite a mesh screen and a curious grad student who was holding some peanuts. In one hand, the student had three peanuts. In the other, eight. The mother baboon could see both hands through the mesh, and she chose the one with eight. The student noted the correct choice. But she also noticed the baby, who followed along and interfered by reaching to make choices itself.
“It was clear that the baby understood what the theme was,” says Jessica Cantlon, who studies the evolution of cognition at Carnegie Mellon and led that Seneca Park Zoo study. In a second version of the test, her team found that even tiny baboon infants, at less than a year old, chose the bigger quantity on their own. The team concluded that both adult baboons and their babies could, in a sense, count.
“They were really, really good,” Cantlon says. “This quantitative ability was something that monkeys have, more or less full-blown, from the time that they're little infants.” She suspected that this was an inside glimpse at some intriguing lesson about evolution, but she couldn’t yet discern what it might be.
For decades, researchers like Cantlon have been studying how animals understand quantities, and they have considered factors ranging from their social group size to diet to total brain volume. Now, drawing from published work on dozens of species, a large team led by Cantlon has found a striking pattern: The density of neurons that an animal has in their cortex predicts its quantitative sense better than any other factor. The work, published in December in Philosophical Transactions of the Royal Society B, shows constraints from evolution—rather than learning or behavior—on cognition. They found that phylogeny, or evolutionary “distance” between species, predicts how well they do at estimating quantities compared to each other. Closely related species tend to have similar levels of skill. Distantly related ones may vary widely.
“It's an impressive study because of the enormous amount of data and all the different factors that they took into account,” says Sarah Brosnan, who researches animal decisionmaking at Georgia State University.
To Brosnan, the results justify a new wave of research into why some species evolved different cognition—and what that might say about humans. Maybe the reason we’re good at understanding quantities isn’t simply that we are primates. If neural density is indeed the critical factor, that trait might be shared by vastly different species with vastly different brains. “Just because you're a primate doesn't mean you're the brightest,” Brosnan says. And if having a primate brain isn’t the gold standard for abstract skills that it was once made out to be, she asks, “What is it that’s driving intelligence and cognition?”
It has not been long since researchers discovered that animals can compare quantities of things. “Thirty or 40 years ago, people were curious: Could animals do it at all?” Cantlon says.
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Since then, evidence has poured in from every corner of the animal kingdom. Desert ants navigate by tracking the steps they take. Spotted hyenas estimate the number of their opponents before interacting to suss out any numerical advantage. Lions do, too. Crows grasp the concept of “zero.” Baboon troops travel democratically—opting for whichever direction most of them are heading. (There’s a key caveat to all these experiments, Cantlon points out: As far as we know, animals aren’t counting, the way a person would tally numbers, since that requires a symbolic language for math. They’re estimating differences.)
Much of researchers' interest originates from questions about human development, in what could have catalyzed our more sophisticated sense of numbers. “We look in the domain of mathematics a lot, because that's an area where humans seem unique,” says Cantlon. “How different are we? And how different are human children from other species when they're 4 and 5 years old?”
But it’s hard to compare skills across animal species. Study methodologies vary, so they are not always scientifically compatible, especially the more elaborate ones. For their own analysis, Cantlon’s team needed to find a task common enough to have been repeated in experiments among a diverse set of species. They settled on a simple task in which researchers offer animals two piles of treats. One pile contains more than the other, like the olive baboon’s peanuts. This type of task has appeared in 49 different studies from around the world, involving 672 individual animals across 33 species. If a parrot, dolphin, horse, or whatever statistically favors piles with more items, then researchers conclude that they likely are able to estimate those quantities. The average sensitivity across species seems to be around 2:1 ratios—they will choose 10 over five, but seven versus five gets fuzzier.
Scientists have historically argued that behavior—learning and development—turned mathless brains into biological calculators. But those arguments undervalue the effects of evolution, Cantlon says, which can influence how brains are organized. So Margaret Bryer and Sarah Koopman, a postdoc and grad student in Cantlon’s lab, both lead authors on the paper, spoke to the scientists behind some of the 49 studies they assembled for their review, and wrote code designed to investigate any patterns in their data that would relate to evolution. Their scripts compared data from the animal experiments to the species’ phylogeny, a web describing their evolutionary relatedness.
Slowly, a picture began to emerge: Animals who were closer together on the phylogenetic tree tended to perform similarly well in the experiments. Chimps were among the top performers, for example. Their close relatives, bonobos, were too. Lemurs, which are more distantly related to them, performed about average.
But non-primate species clustered on other branches of the phylogenetic tree did well too. Grey parrots and rock doves performed about as well as the chimps, and better than many primates. Overall, the study showed, a key predictor of quantitative skills is being closely related to other animals with those skills—not being a primate or even a mammal. “It means that you can pluck any individual animal out of the world and predict something about how sensitive it is to quantity, just by knowing what species it belongs to.” Cantlon says, “That's new.”
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Phylogeny can only tell scientists so much, though. The team wondered if differences might come down to the animals’ neurophysiology. But they weren’t sure which aspect of the brain to measure.
In the past, researchers often used an animal’s total brain volume as a proxy for cognitive power. Basically, the bigger the better. But when Bryer and Koopman pulled the data, they found a weak correlation between brain size and quantitative sensitivity. They turned to a relatively new metric—cortical neuron density—which tells scientists how many neurons a brain has in its cortex. (The cortex is the outer layer of tissue in mammalian brains and is associated with complex cognition.)
Let’s not mince words: To quickly count the number of neurons per milligram of brain, a researcher has to liquefy it. (“She calls it ‘brain soup,’” Cantlon says of neuroscientist Suzana Herculano-Houzel of Vanderbilt University, who developed the method. “It is literally melting it in chemicals.”) In this case, the researchers used data sets from Herculano-Houzel’s lab, pulling published figures on neuron density for 12 species. Here, the correlation was clear: Neuron density had the biggest effect on quantitative sensitivity among all metrics tested, including traits like home range size and social group size. Since neuron density is largely constrained by a species’ genes, the team sees that as bonus proof that evolution plays a huge role.
The magic of neuron density is that it has consequences for cognition, yet it is surprisingly independent of brain size. For some mammals, larger brains might have larger neurons and thus lower density. But that is by no means a general rule. It’s simply its own thing. Smaller neurons, with smaller branches, can pack together tighter and give a brain a more fine-grained sense of the world. “Think of the number of pixels in a camera: The more pixels, the more resolution,” says Herculano-Houzel, who was not involved in this study.
The new findings are valuable as the field of cognitive science breaks away from old assumptions about evolution, she says. Scientists have historically explained away interspecies variations in cognition with differences in body size, brain volume, or the problematic notion that humans and primates are more evolved than other animals. “There's no one way in nature to build a brain and a body around it,” says Herculano-Houzel. “There is no ideal brain. There's no better brain.”
The Carnegie Mellon team’s results counter old assumptions that primates are cognitively “better” than birds or other vertebrates, agrees Brosnan. “And as a matter of fact, if you look closely, even within smaller taxa, there’s quite a bit of variability,” she says. For example, gorillas are mediocre at the task, despite being great apes. To Brosnan, this suggests a need to study the cognitive abilities of less conventional species, such as reptiles. “What we are seeing suggests that they're really smart,” she says. “We just need to learn more about them."
Still, when it comes to estimating quantities, humans are the top performers. We can do it with around 10 percent precision. Cantlon suspects that the neurological process is very similar for all species, but humans can just do it with a greater degree of sensitivity. It’s a skill that may have led to our ability to count—and perhaps to our symbolic representations of numbers and letters.
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To her, quantitative sensitivity therefore may not just tell the evolutionary story of counting, but of written language. “In the human history of counting and language, the first thing that humans wanted to write down was quantity. And they did it with these little tally sticks,” Cantlon says of artifacts like etched bones dating back to 40,000 years ago. (Ancient writing systems like cuneiform and hieroglyphics are only about 5,000 years old.) “It is sort of telling that when a human goes to record something symbolically for the first time, what they’re recording is quantity.”
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